# Economic Crimes by Category in Latin America (2020-2023)
## Corruption, Money Laundering, Fraud, Tax Evasion and Organized Crime

**Author:** de la Serna, Juan Moises (International University of La Rioja | Behavioral Epigenetics & Neuroeducation Researcher)
**ORCID:** https://orcid.org/0000-0002-8401-8018
**DOI:** https://doi.org/10.7910/DVN/8FXZOJ
**Repository:** Harvard Dataverse
**Version:** V2 (2026-03-20)
**License:** CC0 1.0 Public Domain Dedication

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## Overview

This dataset compiles statistics and estimates on economic crimes across 20 Latin American countries for the period 2020-2023. Data were collected from secondary sources including Transparency International (Corruption Perceptions Index - CPI), Global Financial Integrity (GFI), Inter-American Development Bank (IDB), FATF/GAFI, UNODC, and the PwC Global Economic Crime Survey.

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## Dataset Structure

### MODULE 1 — CORE DATA (3 files)

| File | Variables | Observations | Description |
|------|-----------|--------------|-------------|
| delitos_economicos_latinoamerica_2020_2023.tab | 8 | 146 | Main dataset: all crime categories by country and year |
| delitos_economicos_latinoamerica_2020_2023-1.tab | 8 | 146 | Version 1 of main dataset |
| delitos_economicos_latinoamerica_2020_2023-2.tab | 8 | 59 | Subset by crime category for 20 countries |

### MODULE 2 — DOCUMENTATION (5 files)

| File | Description |
|------|-------------|
| README.md | Complete dataset documentation (this file) |
| CODEBOOK.md | Variable definitions, units, types, sources |
| METHODOLOGY.md | Data collection protocol, AI-search strategy, limitations |
| CHANGELOG.md | Version history log |
| references.tab | Structured bibliography (6 primary sources) |

### MODULE 3 — REPRODUCIBLE CODE (2 files)

| File | Description |
|------|-------------|
| analysis_script.R | R script: CAGR, 5 publication-quality figures (ggplot2) |
| economic_crimes_latam_analysis.ipynb | Python notebook: full analysis, 6 figures (matplotlib/seaborn) |

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## Crime Categories

1. **Corruption** — Transparency International CPI Index (scale 0-100; higher = less corrupt)
2. **Tax Evasion** — % of GDP (Global Financial Integrity / IDB estimates)
3. **Money Laundering** — FATF/GAFI risk level (Low, Medium, High, Very High)
4. **Fraud and Scams** — % of companies affected (PwC Global Economic Crime Survey)
5. **Organized Economic Crime** — Qualitative indicators + homicide rate per 100,000 (UNODC)

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## Countries Covered (20)

Argentina, Brazil, Mexico, Colombia, Chile, Peru, Venezuela, Ecuador, Bolivia, Paraguay,
Uruguay, Guatemala, Honduras, El Salvador, Costa Rica, Panama, Dominican Republic,
Nicaragua, Haiti, Cuba.

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## Data Sources

| Source | Organization | Variable |
|--------|-------------|----------|
| Corruption Perceptions Index | Transparency International | cpi_score |
| Illicit Financial Flows | Global Financial Integrity (GFI) | tax_evasion_gdp_pct |
| Mutual Evaluation Reports | FATF/GAFI | ml_risk_level |
| Global Economic Crime Survey | PwC | fraud_companies_pct |
| Global Study on Homicide | UNODC | homicide_rate |
| Regional Economic Analyses | Inter-American Development Bank (IDB) | tax_evasion_gdp_pct |

Data sourced via AI-assisted searches in Perplexity AI (February 2026) based on official and academic sources, with systematic cross-validation.

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## Data Quality Notes

- Some values are regional estimates or averages where country-specific data was unavailable.
- Qualitative data uses descriptive scales: Low, Medium, High, Very High.
- Venezuela data should be interpreted with caution due to limited official reporting.
- CPI measures perception, not actual corruption levels.
- Consulting primary sources for detailed analyses is recommended.

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## Citation

de la Serna, Juan Moises, 2026, "Economic Crimes by Category in Latin America (2020-2023): Corruption, Money Laundering, Fraud, Tax Evasion and Organized Crime", https://doi.org/10.7910/DVN/8FXZOJ, Harvard Dataverse, V2.